基于移动激光扫描的靶标叶面积计算方法

针对疏枝果园的变量对靶施药问题,提出基于移动激光扫描(Mobile laser scanning,MLS)技术的靶标叶面积计算方法,为变量施药实时提供基础数据。为消除激光雷达(Light detection and ranging,LiDAR)探测距离和施药车辆行驶速度对点云密度的影响,在车辆行驶方向和激光雷达扫描方向上计算每个测量点的分辨率,为MLS点云数据建立变尺度格网,以格网面积作为被激光束覆盖的叶面积,建立靶标总体格网面积(Total grid area,TGA)与真实总体叶面积(Total leaf area,TLA)的线性回归模型。采用仿真树模拟疏枝果树靶标,搭建移动激光扫描测量系统,采集靶标点云数据,改变探测距离及移动速度,获取了4种不同疏枝程度靶标的108个样本数据。试验结果表明,随着探测距离的增加和移动速度的降低,靶标点云数显著减少,变异系数最小为0.9209,靶标格网面积能稳定提取,变异系数最大为0.0537,TGA与TLA的拟合优度为0.9090,叶面积测量相对误差均值为9.16%。

Calculation Method of Target Leaf Area Based on Mobile Laser Scanning

Aiming to solve the problem of variable-rate pesticide spraying in sparse branch orchard, a method of target leaf area calculation based on mobile laser scanning (MLS) technology was proposed to provide basic data for real-time variable-rate pesticide spraying. To eliminate the influence of LiDAR detection distance and vehicle speed on the density of point cloud, the resolution of each measurement point in vehicle moving direction and LiDAR scanning direction was calculated, and the variable-scale grid was established for MLS point cloud data. The grid area was taken as the leaf area covered by laser beam, and the regression model of real total leaf area (TLA) and total grid area (TGA) was established. In the experiment, simulation tree was used to simulate the target of thinning fruit trees, and an MLS measurement system was built to collect the cloud data of the target points. Through changing the detection distance and moving speed, totally 108 sample data for four targets with different thinning degrees were obtained. The experimental results showed that the number of target cloud was decreased significantly with the increase of detection distance and the decrease of moving speed with variation coefficient over 0.9209, while the area of target grid can be extracted stably with variation coefficient less than 0.0537. The r-squared of linear fitting of TLA and TGA was 0.9090, and the mean value of relative error of TLA measurement was 9.16%.